CN117597220A - Diagnostic system - Google Patents
Diagnostic system Download PDFInfo
- Publication number
- CN117597220A CN117597220A CN202280031031.6A CN202280031031A CN117597220A CN 117597220 A CN117597220 A CN 117597220A CN 202280031031 A CN202280031031 A CN 202280031031A CN 117597220 A CN117597220 A CN 117597220A
- Authority
- CN
- China
- Prior art keywords
- sensor
- detection result
- unit
- time point
- degradation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 claims abstract description 147
- 238000004088 simulation Methods 0.000 claims abstract description 46
- 230000015556 catabolic process Effects 0.000 claims description 72
- 238000006731 degradation reaction Methods 0.000 claims description 72
- 230000009471 action Effects 0.000 claims description 2
- 238000003745 diagnosis Methods 0.000 description 30
- 238000012986 modification Methods 0.000 description 20
- 230000004048 modification Effects 0.000 description 20
- 238000004891 communication Methods 0.000 description 14
- 238000012545 processing Methods 0.000 description 14
- 238000009434 installation Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 11
- 238000000034 method Methods 0.000 description 11
- 238000010248 power generation Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 230000006866 deterioration Effects 0.000 description 7
- 230000002159 abnormal effect Effects 0.000 description 6
- 230000005856 abnormality Effects 0.000 description 6
- 238000005259 measurement Methods 0.000 description 6
- 239000000523 sample Substances 0.000 description 6
- 238000013178 mathematical model Methods 0.000 description 5
- 230000005611 electricity Effects 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 2
- 239000003990 capacitor Substances 0.000 description 2
- 239000000470 constituent Substances 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 229910001416 lithium ion Inorganic materials 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- JJWKPURADFRFRB-UHFFFAOYSA-N carbonyl sulfide Chemical compound O=C=S JJWKPURADFRFRB-UHFFFAOYSA-N 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 239000000843 powder Substances 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
- B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
- B25J13/085—Force or torque sensors
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/06—Safety devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1671—Programme controls characterised by programming, planning systems for manipulators characterised by simulation, either to verify existing program or to create and verify new program, CAD/CAM oriented, graphic oriented programming systems
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
- G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
- G05B2219/39412—Diagnostic of robot, estimation of parameters
Abstract
A diagnostic system (10) acquires operation condition information capable of identifying operation conditions of a robot arm (12). The diagnostic system (10) acquires detection results of a plurality of sensor devices (20) provided to the robot arm (12). The diagnostic system (10) estimates the detection result at the second time point of a specific sensor device (20) among the plurality of sensor devices (20) by inputting the operation condition information acquired at the first time point and the detection results of the plurality of sensor devices (20) acquired at the first time point to the simulation model. The diagnostic system (10) compares the estimated detection result of the specific sensor device (20) at the second time point with the detection result of the specific sensor device (20) acquired at the second time point to estimate the state of the specific sensor device (20).
Description
Technical Field
The present invention relates to data processing technology, and in particular, to a diagnostic system.
Background
Patent document 1 below discloses a working device in which an estimating unit estimates the direction and magnitude of the force detected by a first force detecting unit based on the detection result of a second force detecting unit, and an abnormality determining unit determines whether or not at least one of the first force detecting unit and the second force detecting unit is abnormal by comparing the estimation result of the estimating unit with the detection result of the first force detecting unit.
Prior art literature
Patent literature
Patent document 1: japanese patent laid-open No. 2020-39397
Disclosure of Invention
Problems to be solved by the invention
The technique disclosed in patent document 1 is a technique of estimating the detection result of the second sensor from the detection result of the first sensor, and improvement of the estimation accuracy is demanded.
The present invention has been made in view of the above-described problems, and an object thereof is to provide a technique for improving accuracy of estimation of a detection result of a sensor provided in a device having a movable portion driven by a driving force.
Solution for solving the problem
In order to solve the above problems, a diagnostic system according to an embodiment of the present invention includes: an operation condition information acquisition unit that acquires operation condition information capable of identifying an operation condition of an apparatus having a movable unit driven by a driving force; a detection result acquisition unit that acquires detection results of a plurality of sensors provided in a device; a detection result estimation unit that estimates a detection result at a second time point of a specific sensor among the plurality of sensors by inputting the operation condition information acquired at the first time point and the detection results of the plurality of sensors acquired at the first time point to the simulation model; and a sensor state estimating unit that compares the detection result of the specific sensor at the estimated second time point with the detection result of the specific sensor from among the plurality of sensors acquired at the second time point to estimate the state of the specific sensor.
Any combination of the above-described components, and a method of converting the expression of the present invention between an apparatus, a method, a computer program, a recording medium storing the computer program, and the like are also effective as the method of the present invention.
ADVANTAGEOUS EFFECTS OF INVENTION
According to the present invention, the accuracy of estimating the detection result of the sensor provided in the device having the movable portion driven by the driving force can be improved.
Drawings
Fig. 1 is a diagram showing the structure of a diagnostic system of the first embodiment.
Fig. 2 is a block diagram showing functional blocks of the sensor device of the first embodiment.
Fig. 3 is a block diagram showing functional blocks of the diagnostic apparatus of the first embodiment.
Fig. 4 is a flowchart showing the operation of the diagnostic system of the first embodiment.
Fig. 5 is a block diagram showing functional blocks of the diagnostic apparatus of the second embodiment.
Fig. 6 is a flowchart showing the operation of the diagnostic system of the second embodiment.
Detailed Description
A summary of the embodiments is described. In order to be able to diagnose the state of equipment such as a machine tool from a remote place, sensor settings for the equipment are being developed. However, in order to perform an appropriate diagnosis for the sensor, it is necessary to determine with high accuracy whether the sensor is in a trusted state. In an embodiment, one technique is presented as follows: in a diagnostic system that estimates a detection result of a sensor provided in a device and uses the estimation result to estimate the state of the sensor, the detection result of the sensor is estimated in consideration of the operation condition of the device. This improves the accuracy of estimating the detection result of the sensor and improves the estimation result of the state of the sensor.
< first embodiment >
Fig. 1 shows the structure of a diagnostic system 10 of a first embodiment. The diagnostic system 10 diagnoses a state of a sensor provided in a device (in the first embodiment, the robot arm 12) having a movable portion driven by receiving a driving force. The robot arm 12 includes a first movable portion 14a, a second movable portion 14b, and a third movable portion 14c (hereinafter, collectively referred to as "movable portions 14"). Each of the plurality of movable portions 14 includes a mechanical element, such as a joint member, driven by a driving force such as hydraulic pressure or electric power. The robot arm 12 of the embodiment includes three movable portions 14 to perform the triaxial operation, but as a modification, the robot arm 12 may include six movable portions 14 to perform the six-axis operation.
The robot arm 12 further includes a first link 16a, a second link 16b, and a third link 16c (collectively referred to as "links 16"). The first link 16a is a link member that connects the first movable portion 14a and the second movable portion 14 b. The second link 16b is a link member that connects the second movable portion 14b and the third movable portion 14 c. The third link 16c is a link member that is positioned further forward than the third movable portion 14 c.
The robot arm control device 18 transmits a first control signal for controlling the operation of the first movable unit 14a to the first movable unit 14a based on the posture, the operation, and the like to be performed by the robot arm 12. The robot arm control device 18 transmits a second control signal for controlling the operation of the second movable portion 14b to the second movable portion 14 b. The robot arm control device 18 transmits a third control signal for controlling the operation of the third movable unit 14c to the third movable unit 14 c. Each of the first control signal, the second control signal, and the third control signal includes operation condition information that determines an operation condition of each movable unit 14. The operation condition includes, for example, data for specifying or prescribing a mode (for example, a speed, an angle, an angular velocity, an acceleration, an operation time, and the like) of the operation of the movable unit 14.
The diagnostic system 10 is a bypass system that is constructed independently of the main system related to the motion of the robot arm 12, and can be added to an existing main system later. The diagnostic system 10 includes a first sensor device 20a, a second sensor device 20b, a third sensor device 20c, and a diagnostic device 22. When the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c are collectively referred to as "sensor devices 20".
Fig. 2 is a block diagram showing functional blocks of the sensor device 20 of the first embodiment. The blocks shown in the block diagrams of the present specification can be realized in hardware by a processor, a CPU, a memory, and other elements of a computer, an electronic circuit, and a mechanical device, and can be realized in software by a computer program, etc., but functional blocks realized by cooperation of these blocks are described herein. Thus, those skilled in the art will appreciate that these functional blocks can be implemented in various forms by a combination of hardware and software.
The sensor device 20 is mounted as a label on the surface of an article (hereinafter also referred to as an "object") having a predetermined physical structure. The object may be various electronic devices, electrical devices, mechanical devices, components, or finished products. In the first embodiment, the plurality of sensor devices 20 are provided to the link 16 of the robot arm 12, but as a modification, at least a part of the plurality of sensor devices 20 may be provided to the movable portion 14 of the robot arm 12. The sensor device 20 includes a detection unit 30, a processing unit 32, an environment power generation unit 34, a power storage unit 36, and an antenna 38.
The sensor device 20 displays various information on the object on the outer surface (the print surface in fig. 2) as a label. In the sensor device 20, members corresponding to the functional blocks shown in fig. 2 are integrally provided in a sheet shape. The sheet-like shape means that the length of the sensor device 20 in the thickness direction is shorter than either the length of the sensor device 20 in the longitudinal direction or the length in the lateral direction. For example, when the length in the longitudinal direction and the length in the lateral direction of the sensor device 20 are several centimeters, the length in the thickness direction of the sensor device 20 is 5 millimeters or less. In addition, the length of the sensor device 20 in the thickness direction is desirably 1 mm or less.
The detector 30 is provided in contact with or in proximity to the object, and measures a state (also referred to as a physical quantity) related to the object. The detecting portion 30 of the first sensor device 20a measures the first sensor device 20a set position in the robot arm 12, that is, in the first embodiment, the state related to the first link 16a in the robot arm 12. The detecting portion 30 of the second sensor device 20b measures the second sensor device 20b set position in the robot arm 12, that is, in the first embodiment, the state related to the second link 16b in the robot arm 12. The detecting portion 30 of the third sensor device 20c measures the third sensor device 20c set position in the robot arm 12, that is, the state related to the third link 16c in the robot arm 12 in the first embodiment.
The state related to the object measured by the detecting unit 30 may be one or both of the state of the object itself (the state of one or both of the inside and the surface of the object) and the state of the surroundings of the object (in other words, the environment surrounding the object). The state related to the object may be one type of physical state or physical quantity, or may be a combination of a plurality of types of physical states or physical quantities. For example, the state related to the object may be vibration (for example, triaxial acceleration) and/or temperature. The state related to the object may be the velocity and/or pressure of the fluid flowing through the power transmission path provided in the object, or may be measured based on the reflected intensity of the ultrasonic wave or the electric wave.
In the first embodiment, the detecting portion 30 measures the vibration of the sensor installation position (also referred to as a sensor installation site). The detection section 30 outputs a signal (also referred to as a "detection signal") based on the measurement result (detection result) to the processing section 32.
The processing section 32 generates information (hereinafter also referred to as "sensor data") output from the antenna 38 based on the measurement result of the detection section 30, that is, based on the detection signal output from the detection section 30 in the embodiment. The processing unit 32 may execute predetermined operations (for example, various filtering processes, abnormality diagnosis processes by an artificial intelligence function, and the like) based on the detection signal output from the detection unit 30, and generate sensor data including the operation result thereof.
The antenna 38 serves as an output unit for outputting sensor data generated by the processing unit 32 in the embodiment, which is data based on the measurement result of the probe unit 30. The antenna 38 may transmit sensor data to an external device by using Wi-Fi (registered trademark), BLE (Bluetooth Low Energy: bluetooth low energy (registered trademark)), NFC (Near Field Communication: near field communication), or the like as a communication unit. In an embodiment, the sensor data sent from the antenna 38 of the sensor device 20 is transmitted to the diagnostic device 22 via a wireless communication network and a wired communication network.
The environment power generation unit 34 converts energy existing in the environment around the sensor device 20 into electric power (so-called environment power generation), and supplies the electric power generated by the power generation as electric power for operating each functional block of the sensor device 20. The environment power generation unit 34 may perform well-known environment power generation based on at least one of the energy of electric waves such as temperature, humidity, wi-Fi, etc., electromagnetic waves (including radiation rays and cosmic rays, and electromagnetic noise emitted from an electric motor, etc.), vibration, sound (including ultrasonic waves), light (including visible light, infrared light, ultraviolet light), and fluid or powder flow (wind, wave, etc.). In addition, the antenna 38 may also include the function of the environment power generation section 34, in which case the antenna 38 may also perform data communication and environment power generation in a time-sharing manner.
The power storage unit 36 accumulates the electricity generated by the environment power generation unit 34, and supplies the accumulated electricity as electricity for operating the functional blocks of the sensor device 20. In the embodiment, the detection unit 30, the processing unit 32, and the antenna 38 of the sensor device 20 can operate based on the electric power supplied from the environment power generation unit 34, or can operate using the electric power supplied from the power storage unit 36. The power storage unit 36 may be a capacitor (including an electric double layer capacitor), or may be a secondary battery (e.g., a lithium ion battery, a solid lithium ion battery, or an air battery).
Referring back to fig. 1, the diagnostic device 22 is an information processing device connected to the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c via a wireless communication network and a wired communication network including an access point, a switch, a router, and the like, which are not shown. The diagnostic device 22 performs data processing for diagnosing the state of a specific sensor device 20 among the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c. Hereinafter, the specific sensor device 20 to be the object of the diagnosis state is referred to as a "diagnosis object sensor". The diagnosis target sensor in the first embodiment is the third sensor device 20c.
Fig. 3 is a block diagram showing functional blocks of the diagnostic device 22 of the first embodiment. The diagnostic device 22 includes a control unit 40, a storage unit 42, and a communication unit 44. The control section 40 performs various data processing. The storage unit 42 stores data referred to or updated by the control unit 40. The communication unit 44 communicates with an external device according to a predetermined communication protocol. In the first embodiment, the control unit 40 transmits and receives data to and from the robot arm control device 18, the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c via the communication unit 44.
The storage section 42 includes a model storage section 46 and a diagnostic information storage section 48. The model storage unit 46 stores data of a simulation model for estimating the detection result of the diagnosis target sensor. Details of the simulation model are described later. The diagnostic information storage unit 48 stores diagnostic information indicating the estimation result concerning the state of the sensor to be diagnosed. The diagnostic information may include information indicating the state (for example, normal or abnormal) of the diagnostic target sensor and information indicating the date and time at which the state of the diagnostic target sensor was diagnosed as the diagnostic result.
The control unit 40 includes an operation condition information acquisition unit 50, a detection result acquisition unit 52, a detection result estimation unit 54, a sensor state estimation unit 56, and a diagnostic information providing unit 58. The computer program having the functions of the plurality of functional blocks may be stored in a predetermined recording medium, or may be installed in a storage device of the diagnostic device 22 via the recording medium. The computer program may be downloaded and installed in the storage device of the diagnostic device 22 via a communication network. The CPU of the diagnostic device 22 may perform the functions of the respective functional blocks by reading the computer program from the main memory and executing the computer program.
The operation condition information acquisition unit 50 acquires, from the robot arm control device 18, a plurality of pieces of operation condition information (first control signal, second control signal, third control signal in the first embodiment) which are transmitted from the robot arm control device 18 to the robot arm 12 and which can identify the operation conditions of the plurality of movable units 14. As a modification, the operation condition information acquisition unit 50 may acquire the plurality of pieces of operation condition information transmitted from the arm control device 18 from the arm 12, or may acquire the plurality of pieces of operation condition information transmitted from the arm control device 18 from a relay device (not shown) that relays communication between the arm control device 18 and the arm 12.
The detection result acquisition unit 52 acquires detection results of the plurality of sensor devices 20 provided in the robot arm 12. Specifically, the detection result acquisition unit 52 acquires first sensor data indicating the detection result of the first sensor device 20a transmitted from the first sensor device 20a, second sensor data indicating the detection result of the second sensor device 20b transmitted from the second sensor device 20b, and third sensor data indicating the detection result of the third sensor device 20c transmitted from the third sensor device 20c. The first sensor data, the second sensor data, and the third sensor data of the first embodiment each contain information (e.g., amplitude and frequency) related to vibration of the sensor setting position.
Here, the simulation model of the first embodiment is explained. The simulation model is a mathematical model that receives as input the operation condition information acquired at a first time point and the detection results (vibration information in the first embodiment) of the plurality of sensor devices 20 represented by the plurality of sensor data acquired at the first time point, and estimates the detection results of the diagnosis target sensor determined in advance in the plurality of sensor devices 20 at a second time point. The mathematical model can be said to be a computational expression or a function. The simulation model may be a so-called digital twin model that simulates the operation of the movable portion 14 of the robot arm 12 and the detection result of the sensor device 20. The second time point in the first embodiment is set to be the same time point as the first time point, but as a modification, the second time point may be a time point later than the first time point.
The simulation model of the first embodiment is a mathematical model of the operation conditions inputted into the plurality of movable units 14. In addition, the simulation model of the first embodiment is a mathematical model of the detection results of the sensor devices 20 other than the diagnosis target sensor, which are input to the plurality of sensor devices 20. For example, the simulation model may be a regression equation in which the operation condition indicated by the first control signal, the operation condition indicated by the second control signal, the operation condition indicated by the third control signal, the detection result of the first sensor device 20a indicated by the first sensor data, and the detection result of the second sensor device 20b indicated by the second sensor data are used as explanatory variables, and the detection result of the third sensor device 20c, which is the diagnosis target sensor, is used as target variables.
In the simulation model of the first embodiment, the actual value sets of the operation conditions indicated by the first control signal, the operation conditions indicated by the second control signal, the operation conditions indicated by the third control signal, the detection results of the first sensor device 20a indicated by the first sensor data, the detection results of the second sensor device 20b indicated by the second sensor data, and the detection results of the third sensor device 20c indicated by the third sensor data may be collected as sample data. Further, the data of the simulation model may be generated by determining the coefficients of the respective explanatory variables by performing multiple regression analysis based on a plurality of sample data.
The detection result estimating unit 54 reads out the data of the simulation model stored in the model storage unit 46, and inputs the operation condition information acquired at the first time point and the detection results of the plurality of sensor devices 20 acquired at the first time point to the simulation model, thereby estimating the detection result at the second time point of the diagnosis target sensor. In the first embodiment, the detection result estimation unit 54 inputs the operation conditions of the plurality of movable units 14 to the simulation model. The detection result estimating unit 54 inputs the detection results of the sensors other than the diagnosis target sensor in the plurality of sensor devices 20 to the simulation model.
Specifically, the detection result estimating unit 54 inputs the operation condition indicated by the first control signal, the operation condition indicated by the second control signal, and the operation condition indicated by the third control signal acquired at the first time point into the simulation model. The detection result estimating unit 54 inputs the detection result of the first sensor device 20a indicated by the first sensor data acquired at the first time point and the detection result of the second sensor device 20b indicated by the second sensor data to the simulation model. Then, the detection result estimating unit 54 acquires the detection result (in the first embodiment, the estimated value concerning the vibration) of the third sensor device 20c, which is the diagnosis target sensor, at the second time point, which is output from the simulation model.
The sensor state estimating unit 56 compares the detection result of the diagnosis target sensor at the second time point estimated by the detection result estimating unit 54 with the detection result of the diagnosis target sensor acquired at the second time point, and estimates the state of the diagnosis target sensor.
In the first embodiment, the sensor state estimating section 56 compares the estimated value of the detection result of the third sensor device 20c at the second time point, which is the detection result of the diagnosis target sensor at the second time point, with the actual detection result (measurement value) of the third sensor device 20c represented by the third sensor data acquired at the second time point, which is the detection result of the diagnosis target sensor acquired at the second time point. When the difference between the estimated value of the detection result of the third sensor device 20c and the actual detection result (measurement value) of the third sensor device 20c falls outside the predetermined allowable range, the sensor state estimating unit 56 estimates that the state of the third sensor device 20c is abnormal. The allowable range may be determined to be an appropriate value according to the knowledge of the developer of the diagnostic system 10 and the experiment using the diagnostic system 10 (for example, the experiment using the normal third sensor device 20c and the abnormal third sensor device 20c, respectively).
The sensor state estimating unit 56 stores diagnostic information including the estimation result and the estimated date and time of the state of the diagnosis target sensor in the diagnostic information storage unit 48. In response to a request from the outside, the diagnostic information providing unit 58 transmits the diagnostic information stored in the diagnostic information storage unit 48 to an external device (for example, a terminal of a maintainer) not shown, or the diagnostic information providing unit 58 periodically transmits the diagnostic information stored in the diagnostic information storage unit 48 to an external device (for example, a terminal of a maintainer) not shown.
The operation of the diagnostic system 10 of the first embodiment based on the above configuration will be described.
Fig. 4 is a flowchart showing the operation of the diagnostic system 10 of the first embodiment. Here, the description will be given assuming that the first time point and the second time point are the same time point.
The detecting portion 30 of the first sensor device 20a periodically detects vibrations of the sensor arrangement position in the robot arm 12. The antenna 38 of the first sensor device 20a transmits first sensor data indicating the detection result of the detection unit 30 to the diagnostic device 22. In parallel with this, the second sensor device 20b also detects the vibration of the sensor installation position, and transmits second sensor data indicating the detection result thereof to the diagnostic device 22. Similarly, the third sensor device 20c detects vibration of the sensor installation position, and transmits third sensor data indicating the detection result to the diagnostic device 22. The detection result acquisition unit 52 of the diagnostic device 22 acquires the first sensor data, the second sensor data, and the third sensor data that are periodically transmitted from the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c (S10).
The operation condition information acquisition unit 50 of the diagnostic device 22 acquires the first control signal, the second control signal, and the third control signal transmitted from the robot control device 18 to the robot 12 from the robot control device 18 at a certain time point (first time point) (S12).
The detection result estimating unit 54 of the diagnostic device 22 inputs the operation condition of the first movable unit 14a indicated by the first control signal acquired by the operation condition information acquiring unit 50 at the first time point, the operation condition of the second movable unit 14b indicated by the second control signal, the operation condition of the third movable unit 14c indicated by the third control signal, the detection result indicated by the first sensor data acquired by the detection result acquiring unit 52 at the first time point, and the detection result indicated by the second sensor data, to the simulation model. The detection result estimating unit 54 acquires the detection result (estimated value) of the diagnosis target sensor (third sensor device 20 c) at the second time point (here, the same time point as the first time point) estimated by the simulation model (S14).
The sensor state estimating unit 56 of the diagnostic device 22 compares the detection result (estimated value) of the third sensor device 20c obtained from the simulation model with the detection result (actual measurement value) indicated by the third sensor data acquired by the detection result acquiring unit 52 at the first time point to estimate the state of the third sensor device 20c, which is the diagnostic object sensor (S16). The sensor state estimating unit 56 stores diagnostic information indicating the estimation result of the state of the third sensor device 20c in the diagnostic information storage unit 48. The diagnostic information providing unit 58 of the diagnostic device 22 provides the external device with the diagnostic information about the third sensor device 20c stored in the diagnostic information storage unit 48 (S18).
According to the diagnostic system 10 of the first embodiment, the detection result of the sensor device 20 as the diagnostic object provided to the robot arm 12 is estimated using the parameters including the operation condition of the movable portion 14 of the robot arm 12, whereby the estimation accuracy thereof can be improved. That is, according to the diagnostic system 10, an estimated value similar to the detection result in the case where the sensor device 20 as the diagnosis target is normal can be obtained. In addition, the accuracy of estimating the state of the sensor device 20 to be diagnosed can be improved.
< second embodiment >
The second embodiment of the present invention will be described mainly with respect to points different from the above-described embodiments, and description of common points will be omitted as appropriate. The features of the second embodiment can of course be combined with the features of the above-described embodiments and modifications. The same reference numerals are given to the same or corresponding components as those of the above-described embodiment among the components of the second embodiment as appropriate.
The structure of the diagnostic system 10 of the second embodiment is the same as that of the diagnostic system 10 of the first embodiment shown in fig. 1. The diagnostic system 10 of the second embodiment also diagnoses the state of the sensor device 20 provided to the robot arm 12, as in the diagnostic system 10 of the first embodiment. Fig. 5 is a block diagram showing functional blocks of the diagnostic device 22 of the second embodiment. The diagnostic device 22 of the second embodiment includes a degradation estimation unit 60 and an update unit 62 in addition to the functional blocks of the diagnostic device 22 of the first embodiment.
The model storage unit 46 stores data of a degradation estimation model for estimating the degradation degree of the robot arm 12, in addition to the data of the simulation model described in the first embodiment. The degradation estimation model is a mathematical model that receives as input a plurality of sensor data (first sensor data, second sensor data, and third sensor data) indicating detection results of the plurality of sensor devices 20, and estimates the degree of degradation of the robot arm 12. The first sensor data, the second sensor data, and the third sensor data of the second embodiment may be information on vibration of the sensor setting position as in the first embodiment.
For example, the degradation estimation model may be a regression equation in which the detection result of the first sensor device 20a indicated by the first sensor data, the detection result of the second sensor device 20b indicated by the second sensor data, and the detection result of the third sensor device 20c indicated by the third sensor data are used as explanatory variables, and the degradation index value indicating the degree of degradation of the robot arm 12 is used as a target variable. In constructing the degradation estimation model, the detection result of the first sensor device 20a, the detection result of the second sensor device 20b, the detection result of the third sensor device 20c, and the degradation degree of the robot arm 12 may be collected as sample data as a set of actual values. Further, the data of the degradation estimation model may be generated by determining the coefficient of each interpretation variable by performing multiple regression analysis based on a plurality of sample data.
The model storage unit 46 stores data of a plurality of simulation models corresponding to the degradation degree of the robot arm 12. The plurality of simulation models may be generated based on sample data (described in the first embodiment) collected from the robot arms 12 having different degradation degrees. The model storage unit 46 may store a plurality of degradation index values in association with a simulation model suitable for the degradation degree indicated by each degradation index value.
The degradation estimation unit 60 estimates the degree of degradation of the robot arm 12 based on the detection results of the plurality of sensor devices 20. Specifically, the degradation estimation unit 60 reads out the data of the degradation estimation model stored in the model storage unit 46, and inputs the detection results of the plurality of sensor devices 20 transmitted from the plurality of sensor devices 20 to the degradation estimation model, thereby estimating the degradation degree of the robot arm 12.
The updating unit 62 updates the simulation model used by the detection result estimating unit 54 based on the degree of degradation of the robot arm 12 estimated by the degradation estimating unit 60. In the second embodiment, data of a simulation model suitable for the degree of deterioration of the robot arm 12 estimated by the deterioration estimating section 60 is read out from a plurality of simulation models stored in the model storing section 46, and the read-out data of the simulation model is transmitted to the detection result estimating section 54.
The detection result estimating unit 54 estimates the detection result of the diagnosis target sensor using the simulation model updated by the updating unit 62, that is, using the simulation model suitable for the degree of degradation of the robot arm 12 transmitted from the updating unit 62 in the second embodiment.
When the degree of degradation of the robot arm 12 is equal to or greater than a predetermined threshold, the sensor state estimating unit 56 estimates the state of the diagnosis target sensor. Further, the detection result estimating unit 54 estimates the detection result of the diagnosis target sensor on the condition that the degree of degradation of the robot arm 12 is equal to or greater than a predetermined threshold, and as a result, the sensor state estimating unit 56 estimates the state of the diagnosis target sensor. The threshold value may be determined to be an appropriate value based on the knowledge of the developer of the diagnostic system 10, an experiment using the diagnostic system 10, or a sensor failure probability for each degree of degradation of the robot arm 12.
The operation of the diagnostic system 10 of the second embodiment having the above configuration will be described.
Fig. 6 is a flowchart showing the operation of the diagnostic system 10 of the second embodiment. As in the first embodiment, the detection result acquisition unit 52 of the diagnostic device 22 acquires the first sensor data, the second sensor data, and the third sensor data that are periodically transmitted from the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c (S20). The degradation estimation unit 60 of the diagnostic device 22 inputs the detection result of the first sensor device 20a indicated by the first sensor data, the detection result of the second sensor device 20b indicated by the second sensor data, and the detection result of the third sensor device 20c indicated by the third sensor data into the degradation estimation model. The degradation estimation unit 60 acquires a degradation index value indicating the degree of degradation of the robot arm 12, which is derived using the degradation estimation model (S22).
The operation condition information acquiring unit 50 of the diagnostic device 22 acquires the first control signal, the second control signal, and the third control signal transmitted from the robot control device 18 to the robot 12 from the robot control device 18 at a certain time point (first time point) (S24). When the degree of degradation of the robot arm 12 is equal to or greater than the predetermined threshold (S26: yes), the updating unit 62 reads out data of a simulation model corresponding to the degree of degradation of the robot arm 12, in other words, data of a simulation model associated with the degradation index value acquired in S22, from the model storage unit 46, and transmits the data to the detection result estimating unit 54 (S28).
The subsequent processing of S30 to S34 is the same as the processing of S14 to S18 of the diagnostic system 10 of the first embodiment shown in fig. 4, and therefore, the description thereof is omitted. If the degree of deterioration of the robot arm 12 is less than the above-described threshold (S26: "NO"), the processing after S28 is skipped. According to the diagnostic system 10 of the second embodiment, by using the simulation model according to the degree of degradation of the robot arm 12, the accuracy of estimation of the detection result of the diagnosis target sensor can be improved. Further, according to the diagnostic system 10, it is possible to efficiently detect an abnormality of the sensor by estimating the state of the diagnosis target sensor when the deterioration of the robot arm 12 is advanced to some extent.
The present invention has been described above based on the first and second embodiments. It will be understood by those skilled in the art that each of the embodiments is an example, and that various modifications are possible in combinations of the components and the processing steps described in each of the embodiments, and that such modifications are also within the scope of the present invention.
As a first modification, a modification related to the second embodiment will be described.
The plurality of sensor devices 20 provided to the robot arm 12 are used to detect vibrations at the respective sensor-provided positions as in the first embodiment. The degradation estimation unit 60 of the diagnostic device 22 compares the vibration convergence time at the sensor setting position calculated based on the detection results of the plurality of sensor devices 20 with the vibration convergence time estimated based on the operation condition information, to estimate the degradation degree of the robot arm 12.
Specifically, the degradation estimation model stored in the model storage unit 46 may receive input of the detection results of each of the plurality of sensor devices 20, and may derive the vibration convergence time (measured value) of the installation position of each sensor device 20. The vibration convergence time may be a time during which the vibration continues, and may be derived based on a known reference. For example, the vibration convergence time is a time from when vibration of a magnitude equal to or larger than a predetermined first threshold is detected to when vibration equal to or smaller than the first threshold and equal to or larger than a second threshold is not detected. The degradation estimation model may receive input of operation condition information represented by each of the first control signal, the second control signal, and the third control signal, and calculate a vibration convergence time (estimated value) of the installation position of each sensor device 20 based on a predetermined evaluation function. The evaluation function outputs vibration convergence time of the sensor setting position associated with each operation condition in advance for the operation condition indicated by the operation condition information.
The degradation estimation model may compare the vibration convergence time (measured value) and the vibration convergence time (estimated value) of each sensor installation position with respect to each of the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c, and estimate the degradation degree of the robot arm 12 based on the comparison result. For example, it may be estimated that the degree of degradation is low when zero or one sensor installation position becomes the vibration convergence time (measured value) > the vibration convergence time (estimated value). In addition, when the vibration convergence time (measured value) > vibration convergence time (estimated value) is set at the two sensor installation positions, it may be estimated that the degree of degradation is moderate. In addition, when the vibration convergence time (measured value) > vibration convergence time (estimated value) is set at the three sensor installation positions, it may be estimated that the degree of degradation is high.
The degradation estimation unit 60 of the diagnostic device 22 inputs the vibration information of the sensor installation position indicated by each of the plurality of sensor data transmitted from the plurality of sensor devices 20 to the degradation estimation model. The degradation estimation unit 60 inputs the operation conditions indicated by the control signals of the first control signal, the second control signal, and the third control signal transmitted from the robot arm control device 18 to the degradation estimation model. Further, the degradation estimation unit 60 acquires an index value indicating the degree of degradation of the robot arm 12 estimated by the degradation estimation model. The subsequent processing is the same as in the second embodiment, and therefore, the description is omitted. According to the structure of this modification, the degree of deterioration of the robot arm 12 can be estimated with high accuracy based on the vibration convergence time of each sensor installation position.
As a second modification, modifications related to both the first embodiment and the second embodiment will be described.
In the first and second embodiments, the sensor device 20 is provided between the plurality of movable portions 14 (the link 16) provided in the robot arm 12, but as a modification, the sensor device 20 may be provided in the plurality of movable portions 14.
As a third modification, another modification related to both the first embodiment and the second embodiment will be described.
In the first and second embodiments, the diagnosis target sensor is set as the third sensor device 20c, but one or more sensor devices 20 of the first sensor device 20a, the second sensor device 20b, and the third sensor device 20c may be set as the diagnosis target sensor. In this case, the model storage unit 46 of the diagnostic apparatus 22 may store a simulation model for estimating the state of each of the diagnostic sensors, which is different for each of the diagnostic sensors. The detection result estimating unit 54 and the sensor state estimating unit 56 may estimate the state of each of the diagnosis target sensors using simulation models corresponding to one or more diagnosis target sensors, respectively.
The sensor device 20 of the above embodiment is provided as a sensor device for a label, but as a modification, the sensor device 20 may be a sheet-type or coin-type sensor device that can be easily attached to an object, instead of a label.
In the embodiment disclosed in the present specification, a part or all of the plurality of functions may be provided in an integrated manner, or a part or all of the plurality of functions may be provided in an integrated manner. Whether the functions are integrated or distributed, they may be configured in a manner that achieves the objects of the invention.
Any combination of the above examples and modifications is also useful as an embodiment of the present invention. The new embodiment produced by the combination has the effects of both the examples and the modifications to be combined. It is also understood by those skilled in the art that the functions to be achieved by the respective constituent elements described in the claims are achieved by the single bodies of the respective constituent elements shown in the embodiments and the modifications or by the cooperation thereof.
The techniques described in the examples and modifications may be determined as follows.
[ item 1]
A diagnostic system is provided with:
an operation condition information acquisition unit that acquires operation condition information capable of identifying an operation condition of an apparatus having a movable unit driven by a driving force;
a detection result acquisition unit that acquires detection results of a plurality of sensors provided in the device;
a detection result estimation unit that estimates a detection result at a second time point of a specific sensor among the plurality of sensors by inputting the motion condition information acquired at a first time point and the detection results of the plurality of sensors acquired at the first time point to a simulation model; and
a sensor state estimating unit that compares the estimated detection result of the specific sensor at the second time point with the detection result of the specific sensor among the plurality of sensors acquired at the second time point, and estimates the state of the specific sensor.
The second time point may be the same time point as the first time point or may be a different time point from the first time point. The sensor state estimating unit may be a sensor abnormality detecting unit that detects an abnormality in the state of the sensor.
According to this diagnostic system, by estimating the detection result of a specific sensor in consideration of the operating condition of the device, the accuracy of estimating the detection result of the sensor can be improved, and the accuracy of estimating the state of the sensor can be improved.
[ item 2]
The diagnostic system according to item 1, wherein,
the apparatus has a plurality of movable parts,
the detection result estimation unit estimates the detection result at the second time point of the specific sensor by inputting the operation conditions of the plurality of movable units into the simulation model.
According to this diagnostic system, when the device has a plurality of movable portions, the detection result of a specific sensor is estimated based on the operation conditions of the plurality of movable portions, so that the accuracy of estimating the detection result of the sensor can be further improved.
[ item 3]
The diagnostic system according to item 1 or 2, wherein,
the detection result estimation unit estimates a detection result at a second time point of the specific sensor by inputting detection results of sensors other than the specific sensor among the plurality of sensors to the simulation model.
According to this diagnostic system, the detection result of a specific sensor, which excludes the possibility of having an abnormal value, enables highly accurate estimation of the abnormal state of the sensor.
[ item 4]
The diagnostic system according to any one of items 1 to 3, wherein,
a degradation estimation section that estimates a degree of degradation of the apparatus based on detection results of the plurality of sensors; and
and an updating unit that updates the simulation model based on the degree of degradation of the device estimated by the degradation estimation unit.
According to this diagnostic system, the accuracy of estimating the detection result of a specific sensor can be improved by using a simulation model corresponding to the degree of degradation of the device.
[ item 5]
The diagnostic system according to item 4, wherein,
the sensor state estimating unit estimates a state of the specific sensor when the degree of degradation of the device estimated by the degradation estimating unit is equal to or greater than a predetermined threshold.
According to the diagnostic system, it is possible to efficiently detect an abnormality of a specific sensor by estimating the state of the sensor in a case where deterioration of the device is advanced.
[ item 6]
The diagnostic system according to item 4 or 5, wherein,
the plurality of sensors detect vibrations at respective set positions,
the degradation estimation section compares a vibration convergence time at a sensor setting position calculated based on detection results of the plurality of sensors with a vibration convergence time estimated based on the action condition information to estimate a degradation degree of the apparatus.
According to this diagnostic system, the degree of deterioration of the apparatus can be estimated with high accuracy based on the vibration convergence time of the sensor setting position.
Industrial applicability
The techniques of this disclosure can be applied to diagnostic systems.
Description of the reference numerals
10: a diagnostic system; 12: a mechanical arm; 14: a movable part; 20: a sensor device; 22: a diagnostic device; 50: an operation condition information acquisition unit; 52: a detection result acquisition unit; 54: a detection result estimation unit; 56: a sensor state estimation unit; 60: a degradation estimation unit; 62: an updating unit.
Claims (6)
1. A diagnostic system is provided with:
an operation condition information acquisition unit that acquires operation condition information capable of identifying an operation condition of an apparatus having a movable unit driven by a driving force;
a detection result acquisition unit that acquires detection results of a plurality of sensors provided in the device;
a detection result estimation unit that estimates a detection result at a second time point of a specific sensor among the plurality of sensors by inputting the motion condition information acquired at a first time point and the detection results of the plurality of sensors acquired at the first time point to a simulation model; and
a sensor state estimating unit that compares the estimated detection result of the specific sensor at the second time point with the detection result of the specific sensor among the plurality of sensors acquired at the second time point, and estimates the state of the specific sensor.
2. The diagnostic system of claim 1, wherein,
the apparatus has a plurality of movable parts,
the detection result estimation unit estimates the detection result at the second time point of the specific sensor by inputting the operation conditions of the plurality of movable units into the simulation model.
3. The diagnostic system according to claim 1 or 2, wherein,
the detection result estimation unit estimates a detection result at a second time point of the specific sensor by inputting detection results of sensors other than the specific sensor among the plurality of sensors to the simulation model.
4. The diagnostic system according to any one of claims 1 to 3, further comprising:
a degradation estimation section that estimates a degree of degradation of the apparatus based on detection results of the plurality of sensors; and
and an updating unit that updates the simulation model based on the degree of degradation of the device estimated by the degradation estimation unit.
5. The diagnostic system of claim 4, wherein,
the sensor state estimating unit estimates a state of the specific sensor when the degree of degradation of the device estimated by the degradation estimating unit is equal to or greater than a predetermined threshold.
6. The diagnostic system of claim 4 or 5, wherein,
the plurality of sensors detect vibrations at respective set positions,
the degradation estimation section compares a vibration convergence time at a sensor setting position calculated based on detection results of the plurality of sensors with a vibration convergence time estimated based on the action condition information to estimate a degradation degree of the apparatus.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2021-073847 | 2021-04-26 | ||
| JP2021073847 | 2021-04-26 | ||
| PCT/JP2022/014953 WO2022230532A1 (en) | 2021-04-26 | 2022-03-28 | Diagnosis system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117597220A true CN117597220A (en) | 2024-02-23 |
Family
ID=83848027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202280031031.6A Pending CN117597220A (en) | 2021-04-26 | 2022-03-28 | Diagnostic system |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20240051140A1 (en) |
| EP (1) | EP4331785A1 (en) |
| JP (1) | JPWO2022230532A1 (en) |
| CN (1) | CN117597220A (en) |
| WO (1) | WO2022230532A1 (en) |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3726058B2 (en) * | 2001-12-28 | 2005-12-14 | 本田技研工業株式会社 | Legged mobile robot and its floor reaction force detection device |
| US20140088766A1 (en) * | 2012-09-21 | 2014-03-27 | United Technologies Corporation | Health management having system level diagnostic feedback and information fusion |
| JP2017177255A (en) * | 2016-03-29 | 2017-10-05 | ソニー株式会社 | Control device and control method |
| WO2018073955A1 (en) * | 2016-10-21 | 2018-04-26 | 日本電気株式会社 | System analysis method, system analysis device, and program |
| JP7016302B2 (en) * | 2018-08-01 | 2022-02-04 | ルネサスエレクトロニクス株式会社 | Information processing equipment, information processing systems, and programs |
| JP2020039397A (en) | 2018-09-06 | 2020-03-19 | 株式会社デンソー | Work device |
| US20210086361A1 (en) * | 2019-09-19 | 2021-03-25 | Hitachi, Ltd. | Anomaly detection for robotic arms using vibration data |
-
2022
- 2022-03-28 WO PCT/JP2022/014953 patent/WO2022230532A1/en active Application Filing
- 2022-03-28 EP EP22795449.2A patent/EP4331785A1/en active Pending
- 2022-03-28 CN CN202280031031.6A patent/CN117597220A/en active Pending
- 2022-03-28 JP JP2023517183A patent/JPWO2022230532A1/ja active Pending
-
2023
- 2023-10-26 US US18/494,969 patent/US20240051140A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| JPWO2022230532A1 (en) | 2022-11-03 |
| EP4331785A1 (en) | 2024-03-06 |
| WO2022230532A1 (en) | 2022-11-03 |
| US20240051140A1 (en) | 2024-02-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110515351B (en) | Abnormality detector | |
| Borgi et al. | Data analytics for predictive maintenance of industrial robots | |
| EP2890528B1 (en) | Monitoring robot sensor consistency | |
| EP1955830B1 (en) | A method and a control system for monitoring the condition of an industrial robot | |
| US9913006B1 (en) | Power-efficient data-load-efficient method of wirelessly monitoring rotating machines | |
| CN113227926A (en) | Condition monitoring device and method for monitoring an electric machine | |
| EP3719600A1 (en) | Control system, factory system, learning system, estimation model generation method, and actuator state estimation method | |
| Er et al. | Approach towards sensor placement, selection and fusion for real-time condition monitoring of precision machines | |
| KR102182226B1 (en) | Failure Detection-Diagnosis System and Method using Thereof | |
| JP2024045515A (en) | Structure diagnosis system, structure diagnosis method, and structure diagnosis program | |
| WO2020195537A1 (en) | Method and system for creating structure state determination model | |
| CN117597220A (en) | Diagnostic system | |
| WO2020195536A1 (en) | Structural anomaly assessment method and anomaly assessment system | |
| KR101487624B1 (en) | Method for controlling robot manipulator device with a redundant dof for detecting abnormal external force | |
| CN112677147A (en) | Event estimation system and event estimation method | |
| KR101997217B1 (en) | Device diagnostic system | |
| Abdullahi et al. | Accelerometer Based Structural Health Monitoring System on the Go: Developing Monitoring Systems with NI LabVIEW. | |
| WO2022230531A1 (en) | Diagnosis system | |
| Khalil et al. | Sensor measurements only with transmissibility operators for fault detection in flexible beams | |
| WO2020054725A1 (en) | Diagnostic apparatus and diagnostic method | |
| CN113984114A (en) | Method for diagnosing abnormality of underwater structure of ocean floating platform | |
| JP2020166819A (en) | Method and system for creating model to discriminate state of structure | |
| JP2021144433A (en) | Structure abnormality discrimination method and abnormality discrimination system | |
| Daniyan et al. | The use of sensor based technology for enhancing maintenance operations | |
| CN116242426B (en) | Large-span space structure health supervision system and method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |